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All Journal Pena Teknik : Jurnal Ilmiah Ilmu-ilmu Teknik Jurnal Teknik Industri Terintegrasi (JUTIN) Journal of Computer and Information System (J-CIS) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Ceddi Journal of Information System and Technology (JST) Journal of Embedded Systems, Security and Intelligent Systems Journal of Mathematics and Applied Statistics
Arsan Kumala Jaya
Politeknik Negeri Samarinda
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Transportation

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Fire Detection and Room Firefighting System Based on IoT Using C4.5 Decision Tree Algorithm Rika Ismayanti; Fara Triadi; Arsan Kumala Jaya; Ade Irawan
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 4 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i4.10685

Abstract

Early fire detection is a critical requirement in indoor safety systems, where delays of only a few seconds can escalate into severe damage and casualties. Conventional devices often rely on single-sensor thresholds, which are highly susceptible to false alarms and unstable performance in dynamic indoor environments. This study develops an Internet of Things (IoT)-based multi-sensor fire detection and autonomous firefighting system integrated with a C4.5 decision tree classifier for real-time hazard recognition and short-term risk prediction. The prototype combines DHT22 temperature, MQ-135 gas, infrared flame, and ultrasonic water-level sensors with an ESP32 microcontroller, servo-controlled nozzle, and pump-based water spraying, all connected to an Android–Firebase platform for remote monitoring. A multivariate time-series dataset of 200 sensor sequences was preprocessed using a five-step sliding-window model and evaluated through 1,000 repeated hold-out trials. The C4.5 classifier achieved a mean accuracy of 84.9%, with peak values exceeding 90%, and clearly separated Safe, Alert, and Danger states, with smoke concentration emerging as the dominant predictor. Experimental tests in a 60 × 40 × 30 cm chamber produced 1–2 s reaction times, eight successful extinguishing events, and four failures attributable to mechanical belt detachment rather than model errors. These findings indicate that interpretable decision-tree models, when combined with IoT sensing and autonomous actuation, can provide a low-cost framework for real-time fire warning and automatic suppression. Future work should address mechanical robustness, extended deployment, and multi-room scalability
Penerapan Alat Pengering Terasi Udang Rebon Menggunakan Metode Research And Development Rizka Tri Wulandari Putri; Agus Triyono; Arsan Kumala Jaya
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 4 No. 3 (2026): Februari 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i3.781

Abstract

Penelitian ini membahas tentang perancangan dan penerapan alat pengering terasi udang rebon otomatis berbasis mikrokontroler ESP32 dengan metode Research and Development (R&D). Tujuan utama dari penelitian ini adalah untuk meningkatkan efisiensi proses pengeringan dan menjaga higienitas produk yang selama ini masih dilakukan secara tradisional dan bergantung pada kondisi cuaca. Alat yang dikembangkan dilengkapi dengan sensor DHT22 untuk membaca suhu dan kelembaban, elemen pemanas 300W sebagai sumber panas, serta kipas DC 12V untuk menjaga sirkulasi udara di dalam box pengering. Sistem bekerja secara otomatis dengan mengatur pemanas dan kipas melalui relay berdasarkan data sensor, sehingga suhu dan kelembaban tetap stabil selama proses pengeringan. Hasil pengujian menunjukkan bahwa alat ini mampu mengurangi waktu pengeringan dari ±3–4 hari (metode tradisional) menjadi ±8 jam, dengan hasil yang lebih bersih dan konsisten. Penggunaan alat ini diharapkan dapat membantu pelaku UMKM dalam meningkatkan produktivitas dan kualitas produk terasi udang rebon secara efisien, higienis, dan berkelanjutan. Kata Kunci: pengering terasi, udang rebon, ESP32, DHT22, R&D, otomatisasi, IoT
Kendali Alat Sterilisasi Sepatu Berbasis Mobile Rakhmad Dhani; Arsan Kumala Jaya; Ahmad Rofiq Hakim
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 9 No. 3 (2026): July
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v9i3.60344

Abstract

Shoes frequently come into contact with floors and the outdoor environment, making them a potential medium for spreading bacteria and viruses. This study aims to design and build an IoT-based shoe sterilization system that can be monitored and controlled via an Android application. The system uses an ESP32 microcontroller, DHT22 temperature and humidity sensor, MC-38 door sensor, and LJ12A3-4-Z/BX proximity sensor. The sterilization process uses a 254 nm UV-C lamp integrated with Firebase Realtime Database. The system can automatically detect shoe types, set a maximum temperature of 34°C for sneakers and 50°C for safety shoes, and automatically turn off the UV-C lamp when the door is opened. Test results show all components worked as designed. The integration of ESP32, Firebase, and the Android app proved to be an effective IoT-based sterilization solution. 
Co-Authors Abdullah Hanif Ade Irawan Agus Triyono Ahmad Fatoni Dwi Putra Ahmad Rofiq Hakim Ahmad Saiful Mutaqi Azis Akbar Hendra Annisa Nurul Puteri Asmaul Husna RS Basir, Azhar Fajerin Biabdillah Fara Triadi Fara Triadi Hanif, Abdullah Hartanto, Subhan Hendra, Akbar Ismayanti, Rika Luthon Adira Mindi Richia Putri Muhammad Ari Rifqi Muhammad Ikhwan Burhan Muhammad Rizal Muhammad Sabirin Hadis Muhammad Sabirin Hadis Priti Shinta Rakhmad Dhani Randy Angriawan Randy Angriawan Rika Ismayanti Rizka Tri Wulandari Putri Subhan Hartanto